• Padmini Murthy

From data chaos to data nirvana - why simple is so complex.

The data chaos


If you're a Revenue Operations or a Performance/Growth Marketing leader - parsing insane volumes of data daily to interpret patterns makes up a good chunk of your workday. And, on some days, you wish you had a wand that magically brought all your data together, formatted and organized it, and made sense of it all. So, at the click of that button, you got a ready-made dashboard for the QBR, leaving you enough time now to think through the business implications of it!


The digital disruption that led to data silos


We hear you, and you're not alone. Digital is here, and it has transformed your revenue and/or marketing game - for the better. It has made everything measurable, fast (think instant gratification), and somewhat fail-proof if you got one important dimension right - and, i.e., making sense of this data.



Sounds simple, but yet, this is perhaps one of the most daunting tasks due to the defining trait of this data - it is chaotic! They are millions if not billions of rows coming at you from many sources: programmatic ads on Doubleclick and other ad platforms, social media channels, your standard CRM and ERP tool stacks like Salesforce and Netsuite, marketing automation tools, first or third-party audience measurement or digital experience platforms, the list is quite huge.


This data is unformatted, heterogeneous, disjointed, and disconnected (in silos) - we call this the dirty data tsunami. And when systems are not talking to each other - you’re caught in the crossfire.


Getting to nirvana - peeling the layers


Like chaos theory (if you've majored in math), these data sources are like systems with random states of disorders, governed by some underlying patterns that need to be decoded to stumble into gold mines. And that process of stumbling into that gold is TOUGH!


Vanilla ETL /ELT solutions, garbage in, garbage out - the first step is to become familiar with the data's nature and behavior. So running a lightning ETL or ELT process to aggregate and unify and pushing a ‘pretty version’ to a data lake or warehouse won’t cut it. There’s a need to understand the behavior and the goal of this data project PRIOR to getting it through the ETL funnel.


Complex business rules, a big unknown in the data puzzle - there are unique and prescriptive business rules around revenue recognition, attribution modeling, lead funnel definition, and such - which are important to account for while parsing data pipelines. Very few tools make it easy for the business people to use them - and they are the folks who really understand these rules.


There's no engineer for that, look, ma, no hands - while the world's data engineering rock stars are flocking to the best data companies of the world, our marketing and business teams are always short-staffed technically! Yes, just when you need those 250 data sources to connect across 25 countries and 75 partners. You are riding solo with enterprise data at scale!


Flaky data, unpredictable APIs - with the 'systems of engagement' growing exponentially, integration into these systems is an arduous exercise, requiring deep know-how on APIs. And trust me, these APIs are known for bad schemas, outages, missing values. The worst part is not being aware of data problems until a stakeholder sees a chart, and it's wrong because a partner feed was failing for three days! Ugh. And don't forget that with volumes of data comes the standard governance and monitoring needs like alerts and logs, if you have the time to parse through them.


Your data gurus bring a data model - a new approach for nirvana


Even though data nirvana sounds like a simple thing to achieve, it is not as you can see. It requires DataOps superpowers to connect all the dots. Not just a tool or a platform BUT a data model. A new way of thinking about this data.


We call this the Switchboard data model. This model brings a trifecta:


1. Proprietary data expertise - unique knowledge of these highly valuable but arcane datasets and how to blend them into the KPIs that help run your business. And now readily adapted for your business.

2. A highly scalable and battle-tested data automation engine - automates and orchestrates thousands of complex workflows and monitors them reliably, at enterprise scale.


3. Data operations best practices - an industry-leading set of best practices and learnings drawing from 20+ person-years of experience working with disparate media datasets and the most sophisticated enterprises. It is made available by trained data experts who partner with you.


With this model at work, the data that goes into the data warehouses is now smart, helping growth, performance, or revenue leaders create the right dashboards and helping to drive the right results! Greater revenue, engagement, and ROI!


At Switchboard, we’ve helped many customers like Meredith, Spotify, OrangeTheory, Ranker, Freestar, Financial Times, and others get to this nirvana state. We can help you too! Talk to one of our data gurus to get started.

Switchboard - Be Data Strong!


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